177 citations · 1.3k across the 60 of their papers we have counts for
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Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
This paper presents a comprehensive comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNN) and Quantum Neural Networks (QNN), juxtaposed against thei…
A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
Roy T. Forestano, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from…
End-to-end deep learning inference with CMSSW via ONNX using docker
Purva Chaudhari, Shravan Chaudhari, Ruchi Chudasama +1
Deep learning techniques have been proven to provide excellent performance for a variety of high-energy physics applications, such as particle identification, event reconstruction…
Deep Learning-Based Spatiotemporal Multi-Event Reconstruction for Delay Line Detectors
Marco Knipfer, Stefan Meier, Jonas Heimerl +2
Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments,…
Kinematic Evidence of an Embedded Protoplanet in HD 142666 Identified by Machine Learning
J. P. Terry, C. Hall, S. Abreau +1
Observations of protoplanetary disks have shown that forming exoplanets leave characteristic imprints on the gas and dust of the disk. In the gas, these forming exoplanets cause de…